Enterprise MQTT broker for real-time industrial IoT and edge-to-cloud data
HiveMQ operates a distributed MQTT platform designed for industrial IoT deployments at scale. The stack spans Kafka, Kubernetes, and a polyglot backend (Java, Kotlin, Node.js, TypeScript), with React frontends — typical for a data-streaming infrastructure company. Hiring velocity is accelerating with 13 roles in the last 30 days, skewed heavily toward engineering (9) and product (6), signaling investment in platform expansion. Active projects center on AI-first product development and test automation, while pain points cluster around scaling product development, operationalizing AI, and data infrastructure modernization — the signature challenges of a maturing infrastructure vendor moving upmarket.
HiveMQ is an industrial IoT and data-streaming platform built on the MQTT standard, enabling enterprises to connect millions of devices and route data in real time across edge and cloud environments. Founded in 2012 and headquartered in Landshut, Germany, the company serves mission-critical operations for large industrial, automotive, and pharmaceutical organizations. The product layer spans data streaming, data intelligence, and agentic capabilities. With 51–200 employees, HiveMQ operates as a public company with global hiring across Germany, United States, Spain, Portugal, Bulgaria, and the United Kingdom.
HiveMQ's backend is built on Java and Kotlin, with Kafka for data streaming, Kubernetes for orchestration, and ArgoCD for deployment automation. Frontends use React with Chakra UI. Testing spans Cypress, Selenium, and Jest. Development uses GitHub Actions and workflow tools including Gong.
HiveMQ's current focus includes an AI-first product development model, modernizing data infrastructure, and scaling test automation with AI-driven scenarios. Pain points center on operationalizing AI at scale, ensuring application resiliency, and improving test coverage and security.
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